Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 923 941 902 937 903 253 94 438 536 321 156 538 169 455 950 975 186 139 211 761
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 253 950 NA 923 186 902 975 538 169 94 211 NA 455 156 903 321 937 438 761 941 536 NA 139
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 3 4 4 1 2 2 5 2 2
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "i" "z" "e" "w" "u" "T" "M" "C" "G" "S"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 1 2 3 4 5 15 16
which( manyNumbersWithNA > 900 )
[1] 2 4 6 7 15 17 20
which( is.na( manyNumbersWithNA ) )
[1] 3 12 22
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 923 941 902 937 903 950 975
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 923 941 902 937 903 950 975
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 923 941 902 937 903 950 975
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "T" "M" "C" "G" "S"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "i" "z" "e" "w" "u"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 8 9 10 12 14
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "large" NA "large" "small" "large" "large" "large" "small" "small" "small" NA "small" "small" "large" "small"
[17] "large" "small" "large" "large" "large" NA "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "large" "UNKNOWN" "large" "small" "large" "large" "large" "small" "small" "small" "UNKNOWN" "small"
[14] "small" "large" "small" "large" "small" "large" "large" "large" "UNKNOWN" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 950 NA 923 0 902 975 538 0 0 0 NA 0 0 903 0 937 0 761 941 536 NA 0
unique( duplicatedNumbers )
[1] 1 3 4 2 5
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 3 4 2 5
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE TRUE FALSE TRUE FALSE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 7
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 975
which.min( manyNumbersWithNA )
[1] 10
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 94
range( manyNumbersWithNA, na.rm = TRUE )
[1] 94 975
manyNumbersWithNA
[1] 253 950 NA 923 186 902 975 538 169 94 211 NA 455 156 903 321 937 438 761 941 536 NA 139
sort( manyNumbersWithNA )
[1] 94 139 156 169 186 211 253 321 438 455 536 538 761 902 903 923 937 941 950 975
sort( manyNumbersWithNA, na.last = TRUE )
[1] 94 139 156 169 186 211 253 321 438 455 536 538 761 902 903 923 937 941 950 975 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 975 950 941 937 923 903 902 761 538 536 455 438 321 253 211 186 169 156 139 94 NA NA NA
manyNumbersWithNA[1:5]
[1] 253 950 NA 923 186
order( manyNumbersWithNA[1:5] )
[1] 5 1 4 2 3
rank( manyNumbersWithNA[1:5] )
[1] 2 4 5 3 1
sort( mixedLetters )
[1] "C" "e" "G" "i" "M" "S" "T" "u" "w" "z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 9.5 5.5 8.0 2.5 5.5 2.5 2.5 2.5 7.0 9.5
rank( manyDuplicates, ties.method = "min" )
[1] 9 5 8 1 5 1 1 1 7 9
rank( manyDuplicates, ties.method = "random" )
[1] 9 6 8 3 5 1 4 2 7 10
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.29462018 0.32483471 -0.25245818 0.96672018 1.06404391
[11] 0.15778373 -0.24556289 -1.00765411 0.09605385 0.45548199
round( v, 0 )
[1] -1 0 0 0 1 0 0 0 1 1 0 0 -1 0 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.3 0.3 -0.3 1.0 1.1 0.2 -0.2 -1.0 0.1 0.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.29 0.32 -0.25 0.97 1.06 0.16 -0.25 -1.01 0.10 0.46
floor( v )
[1] -1 -1 0 0 1 0 0 -1 0 1 0 -1 -2 0 0
ceiling( v )
[1] -1 0 0 1 1 1 1 0 1 2 1 0 -1 1 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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